Managing Quality within a Network of Suppliers Eda Ross Montgomery Melody Hebert April 6, 2011

2 Managing Quality with a Network of Suppliers Defining the Process –Vertex’ Implementation of QbD –Governance Process Commercial Manufacturing at contract manufacturing organizations –Interface with CMO quality systems –Implementation of QbD in batch records Continuous Improvement –Ongoing Risk Management –Knowledge Management Remaining challenges

3 QbD is Implemented in Stages Develop ProductDevelop matrix showing material attributes, IPCs, and process parameter control that ensures CQAs are met Agree on classifications of deviations Perform trending Understand productDevelop real-time release strategy Agree on change classifications Interpret results across trending parameters Develop specificationsDevelop post-approval change strategy Agree on process for including NORs and PARs in batch record Identify opportunities for improvement; implement as appropriate Perform risk AssessmentDevelop “product and process description” strategy for marketing application Agree on overall control strategy Publish trends and metrics Define design spaceDevelop comparability protocol strategy Agree on trending protocol and process Set goals for continuous improvement

4 Governance Process is Critical for Successful Supplier Management Inter-Company Teams Agree on mutual expectations and deliverables for each team Agree on processes for escalation of issues and relationship management Agree on process for –Communication of unexpected results (OOS and OOT) –Conduct of investigations (OOS and OOT) –Degree of oversight expected and type of information to be exchanged –Evaluation metrics and frequency Project Team Steering Committee Cross-project team

5 ©2009 Vertex Pharmaceuticals Incorporated QbD Governance Process is Compatible with Traditional Quality Systems Control Strategy Document Change Control and Other Quality Systems Criticality Analysis Trend Reports (Quarterly and Annual) Risk Assessment Master Batch Record With Quality agreement, ensures cross-company alignment of quality systems

6 Commercial Manufacturing – Managing Quality under QbD at Suppliers with Traditional Quality Systems Vertex Quality systems completely embrace QbD CMO Quality systems should not be different for QbD and “traditional” products –Changes to CMO Quality systems should be minimized –Use change management procedures to drive implementation of changes –Use nonconformance and process monitoring to identify potential changes and drive continuous improvement Vertex drives continuous process improvement with the support of and input from the CMO(s)

7 Implementation at Contract Manufacturing Organizations : Classifying Deviations relative to NORs and PARs Observation (Outside NOR but within Design Space) Deviation (Outside Design Space) Operating/Control Space Edge of Design Space Parameter 1 Predicted Output Parameter 2

8 A Single Approach to Assessing Criticality is Used for all Aspects of the Process

9 ©2009 Vertex Pharmaceuticals Incorporated Implementation at Manufacturing Sites: Classification of Post- Approval Changes is Consistent with SUPAC Major Change Moderate Change Minor Change

10 Implementation of QbD at Contract Manufacturing Organizations: Implementation of QbD in Batch Records Batch records are designed to ensure the process is operated where it performs best –NOR ranges are intended for routine commercial manufacturing The batch record includes the NORs for critical and key process parameters and in process control (IPC) tests Batch record can also include ranges for non-critical parameters Tighter operating ranges or a mid-points may be implemented to avoid excursions outside the NOR or maximize product performance –PARs for critical and key process parameters and IPCs are included or referenced in the batch record This makes the information readily available to manufacturing supervision

11 Risk Management and Continuous Improvement are Achieved Through a Coordinated Trending Process

12 Continuous Improvement: Risk Management and Supplier Management Coordinated approach to evaluation (trending) of –Product performance based on process parameters, IPCs, material attributes –Key performance indicators that may be indicative of product performance or could indicate a trend with Supplier’s systems, e.g. Confirmed OOS Deviations (Major and Minor) Observations Complaints Coordinated, periodic sharing of results with Suppliers –Each supplier reports product performance and key performance indicators to Vertex –Vertex’ conclusions on product performance and key performance indicators are shared with suppliers Coordinated approach to continuously improving product quality and performance

13 ©2009 Vertex Pharmaceuticals Incorporated Trending Protocol Prospective, documented plan for monitoring during routine manufacturing –Critical and key process parameters –Critical and key material attributes –Activities where frequency of failure is above a threshold –Key performance indicators (see previous slide) Predefined responsibility (Vertex or Supplier) for –monitoring –frequency of reporting –statistical tools to be used –thresholds for key performance indicators Describes content of trending report and method for modifying trended parameters

14 ©2009 Vertex Pharmaceuticals Incorporated Trending Report Comprehensive and cumulative –Quarterly reviews –Designed to meet annual product review requirements Trend reported for all product performance measurements and all key performance indicators –Evaluation of observed trend to predicted trend –Evaluation of discrete “events” that can signal other issues –Evaluation of actual vs. predicted frequency of “events” based on risk assessment –Evaluation of upstream material(s) for impact on product performance Conclusion about changes needed to the process, material attributes, operations, or key performance indicators

15 Trending leads to Improvements in Process or Equipment Temperature lowered * Equipment malfunctioned PAR Batch 5 Time Batch 1Batch 2Batch 3 Batch 4 Batch 6 Temperature decreased to control at different target value After equilibration, minor variations in temperature Equipment malfunction resulted in addition of chiller capacity

16 DP Knowledge Management: Correlating Drug Product Assay with Input Material No consistent bias

17 Predictive model built from development runs Good agreement between actual and predicted value Risk Management: Process Understanding Enables Prediction of Product Performance Measured Response

18 Risk Management: Trending Key Performance Indicators Allows Product Optimization Minor Deviations Observations Major Deviations Increased frequency of minor deviations Minor deviations were for isolation time and temperature (non-critical parameter) Filtration capacity increased

19 Knowledge Management Increases efficiency of resource utilization Kaizen process to eliminate waste and focus on value-adding activities Mechanism for data-based discussion of trends Shared goal

20 Challenges – Data Management Need robust processes –To ensure data integrity from source at Supplier to finished report Include error handling and updates/changes to data –To ensure timely availability of data for analysis and trending Ensure scalability of the database(s) –Anticipate differences in terminology in the design phase –Anticipate changes to trending program Build in flexibility –Anticipate commercial volume(s)

21 Challenges – Data Consistency Need Standardized Data and Definitions For Quality Metrics Deviation root cause Failure modes At Vertex and Suppliers For performance metrics

22 Closing Thoughts Focus on key and critical parameters and key performance indicators –Performance is built in Review the Process Regularly –Focus on knowledge improvements –Cover both corrective and preventative actions Plan for change –Programs, people, scale(s) of operation –Include changes to both process and tools Actively Manage Supplier Relationships –Think long-term –Develop and maintain common goals –Share conclusions and responsibility –Actively solicit feedback

23 Acknowledgements Carole Varanelli Geny Doss Trish Hurter Tom Gandek Kelly Tolton Antoinette Paone Drew Barlow Martin Warman